Abstract
This study investigates the future outlook of global rice consumption using dynamic panel data regression (DPD) with penalised fixed effect model. The three main factors affecting rice consumption include previous rice demand, GDP per capita, and world rice price. The data set covers 73 countries that is almost 80% of world rice consumption from 1960 to 2015. We separate these countries into 4 groups based on income levels classified by the World Bank including low income, lower middle-income, upper middle-income, and high income. The results show that, at the global scale, rice consumption is expected to be slightly higher. Such demand is driven by rising demand from the upper middle- and high income countries, while it is offset by the lower demand from lower middle- and low income countries.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Abdullah, A.B., Ito, S., Adhana, K.: Estimate of rice consumption in Asian countries and the world towards 2050. In: Proceedings for Workshop and Conference on Rice in the World at Stake, vol. 2, pp. 28–43 (2006)
Alexandratos, N., Bruinsma, J., et al.: World agriculture towards 2030/2050: the 2012 revision. Technical report, ESA Working paper Rome, FAO (2012)
Arellano, M., Bond, S.: Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 58(2), 277–297 (1991)
Bond, S.R.: Dynamic panel data models: a guide to micro data methods and practice. Port. Econ. J. 1(2), 141–162 (2002)
Carstensen, K., Toubal, F.: Foreign direct investment in Central and Eastern European countries: a dynamic panel analysis. J. Comp. Econ. 32(1), 3–22 (2004)
Food and Agricultural Organization of The United Nation (FAO): Food outlook (2017). http://www.fao.org/3/a-i7343e.pdf
Huang, B.N., Hwang, M.J., Yang, C.W.: Causal relationship between energy consumption and GDP growth revisited: a dynamic panel data approach. Ecol. Econ. 67(1), 41–54 (2008)
Im, K.S., Pesaran, M.H., Shin, Y.: Testing for unit roots in heterogeneous panels. J. Econom. 115(1), 53–74 (2003)
Judson, R.A., Owen, A.L.: Estimating dynamic panel data models: a guide for macroeconomists. Econ. Lett. 65(1), 9–15 (1999)
Kubo, M., Purevdorj, M., et al.: The future of rice production and consumption. J. Food Distrib. Res. 35(1), 128–142 (2004)
Levin, A., Lin, C.F., Chu, C.S.J.: Unit root tests in panel data: asymptotic and finite-sample properties. J. Econom. 108(1), 1–24 (2002)
Lewbel, A.: Engel curves. In: The New Palgrave Dictionary of Economics, 2 edn. (2008)
Lio, M.C., Liu, M.C., Ou, Y.P.: Can the internet reduce corruption? A cross-country study based on dynamic panel data models. Gov. Inf. Q. 28(1), 47–53 (2011)
Mohanty, S.: Trends in global rice consumption. Rice Today 12(1), 44–45 (2013)
Nicholson, W., Snyder, C.M.: Intermediate Microeconomics and Its Application. Cengage Learning (2014)
Sequeira, T.N., Maçãs Nunes, P.: Does tourism influence economic growth? A dynamic panel data approach. Appl. Econ. 40(18), 2431–2441 (2008)
Sirikanchanarak, D., Liu, J., Sriboonchitta, S., Xie, J.: Analysis of transmission and co-movement of rice export prices between Thailand and Vietnam, pp. 333–346 (2016)
Smil, V., et al.: Feeding the world: how much more rice do we need. In: Rice is Life: Scientific Perspectives for the 21st Century, pp. 21–23 (2005)
The International Rice Research Institute (IRRI): Bigger harvest a cleaner planet (2000). http://www.irri.org/publications/annual/pdfs/ar2000/biggerharvests.pdf
Timmer, C.P., Block, S., Dawe, D.: Long-run dynamics of rice consumption, 1960–2050. In: Rice in the Global Economy: Strategic Research and Policy Issues for Food Security, pp. 139–174 (2010)
United Nations: World population to 2300. United Nations, New York (2004)
United States of Agricultural Department (USDA): Rice: world markets and trade (2017). https://apps.fas.usda.gov/psdonline/circulars/grain.pdf
Zhang, C., Zhuang, L.: The composition of human capital and economic growth: evidence from china using dynamic panel data analysis. China Econ. Rev. 22(1), 165–171 (2011)
Acknowledgements
The first author is grateful to the full scholarship from the Bank of Thailand. In addition, she would like to express much of her appreciations to Mr. Tanarat Rattanadamrongaksorn for his encouragement in bringing this interesting issue to our attention. Also, the second and third authors wish to thank the Puey Ungphakorn Centre of Excellence in Econometrics, Faculty of Economics, Chiang Mai University for giving them financial supports.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Sirikanchanarak, D., Tungtrakul, T., Sriboonchitta, S. (2018). The Future of Global Rice Consumption: Evidence from Dynamic Panel Data Approach. In: Kreinovich, V., Sriboonchitta, S., Chakpitak, N. (eds) Predictive Econometrics and Big Data. TES 2018. Studies in Computational Intelligence, vol 753. Springer, Cham. https://doi.org/10.1007/978-3-319-70942-0_45
Download citation
DOI: https://doi.org/10.1007/978-3-319-70942-0_45
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70941-3
Online ISBN: 978-3-319-70942-0
eBook Packages: EngineeringEngineering (R0)